Field of Invention
This invention relates to data processing systems, and techniques for modelling and analysing the behaviour of physical systems.
Related Art
In designing products such as aircraft, boats, road vehicles, and other complex machinery or electronic systems such as integrated circuits and discrete electronics components it is often desirable to model a candidate design and/or its operating environment, so as to be able to predict the behaviour of the design and, if necessary, identify areas for improvement. In modern design processes, simulations of this nature have replaced many instances where in the past tests would have been carried out on models or physical prototypes. Similar modelling tasks arise in other fields such as predicting sports performance and studying animal behaviour. Some relatively simple physical systems can be modelled efficiently by writing a comprehensive algorithmic model of the system's behaviour and then executing that model using a computer. This approach works well with systems that are well characterised mathematically and are not subject to change. For more complex systems this approach has a number of limitations.
To illustrate this, consider the example of modelling the behaviour of a high performance aircraft.
First, the modelling process is complicated by the fact that the aircraft may have a range of options such as external elements having differing aerodynamic properties, engines of different levels of performance, and different possible fuel loads; and the aircraft may need to be simulated under a range of conditions such as different ambient temperatures, air pressures and payloads. The choice of one option may influence the behaviour of another other option: for example the choice of a certain payload may influence the airflow over a chosen wing and hence the aerodynamic performance of the wing.
Second, the process of estimating the behaviour of the aircraft under certain options and conditions may be highly computationally intensive, meaning it is not feasible to immediately run a simulation, modelling or verification task on an arbitrary set of options and conditions: it may first be necessary to run a complex program requiring significant processor time in order to compute the predicted behaviour of the aircraft with the selected combination of options and conditions.
Third, the process of simply characterising the available options may involve significant work. For example, at the design stage a wing design may be characterised by data defining a set of curved shapes, a payload may be characterised by data defining a set of surface coefficients, mass and cross-section and an engine design may be characterised by data defining values such as power, fuel usage and component weights. These options all involve different parameters which must be brought together to contribute to the overall model of the aircraft when those options are selected. This involves a step additional to the fundamental design process. It will be appreciated that these difficulties are substantial obstacles to developing a working model of a changeable physical system such as an aircraft, a sports car or an ecological environment.
One way to address this problem might be to model each element individually, to store the models and then to combine them when options are selected so as to form an overall model. However, this would not yield an accurate result when the selection of one option has an effect on the behaviour of another option: for example when a payload influences airflow over a wing, or when a reduction in weight due to fuel consumption influences climb performance.
Another way to address the problem might be to develop models for each possible combination of options in advance, and then to invoke the appropriate model when a set of options has been designated for a simulation. However, the total number of possible combinations may be immense, and the amount of processor time needed to develop a model for each one may be significant, so this is not a practical solution.
Finally, whilst it might not be practical to develop a complete model of the physical system in advance of options being selected, it might at least be feasible to bring the disparate design data together manually to form a coherent set of the available options. However, even this would be a substantial task for a complex physical system, and it would need to be repeated as soon as further options became available, which might happen many times during the designing of a complex product.
There is a need for an improved system for processing data defining behaviour of physical systems.